INFO 2950

Last Updated

  • Schedule of Classes - June 18, 2018 7:14PM EDT
  • Course Catalog - June 14, 2018 7:15PM EDT

INFO 2950
Introduction to Data Science

Course information provided by the Courses of Study 2017-2018.

Teaches basic mathematical methods for information science, with applications to data science. Topics include discrete probability, Bayesian methods, graph theory, power law distributions, Markov models, and hidden Markov models. Uses examples and applications from various areas of information science such as the structure of the web, genomics, social networks, natural language processing, and signal processing.  Assignments require python programming.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: A strong performance in an introductory statistics course from the approved list of accepted statistics courses found at http://infosci.cornell.edu/academics/degrees/ba-college-arts-sciences/degree-requirements/core-requirements and an introductory programming class with an ability to write and debug programs, or permission of instructor.

Distribution Category (MQR-AS)

View Enrollment Information

Syllabi:

  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 4 Credits Stdnt Opt

  • 12148 INFO 2950   LEC 001

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  • Information Science majors must complete this class prior to their senior year. If you would like to enroll in this class, but are unable to, please contact the instructor via email at phg5@cornell.edu

  • 17426 INFO 2950   DIS 201

  • Instructor Consent Required (Add)

  • 17893 INFO 2950   DIS 202

  • Instructor Consent Required (Add)

  • 17894 INFO 2950   DIS 203

  • Instructor Consent Required (Add)

  • 17895 INFO 2950   DIS 204

  • Instructor Consent Required (Add)

  • 18246 INFO 2950   DIS 205

  • Instructor Consent Required (Add)

  • 18423 INFO 2950   DIS 206

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